Margaret W. Matlin, Cognition, 8eOutline Chapter 12Page 1 of 13
CHAPTER 12
Deductive Reasoning and Decision Making
Chapter Introduction
thinking—going beyond the information given in order to reach a goal
deductive reasoning—given some specific premises, judge whether those premises allow you to draw a particular conclusion, based on the principles of logic
decision making—assessing and choosing among several alternatives
dual-process theory (for deductive reasoning and decision making)
Type 1 processing—fast and automatic
Type 2 processing—slow and controlled
Deductive Reasoning
conditional reasoning task (propositional reasoning task)—describes the relationship between conditions; "if . . . then . . ."; judged as valid or invalid; focus of Chapter 12
syllogism—two statements that we must assume to be true, plus a conclusion; "all, none, some . . ."; judged as valid, invalid, or indeterminate
An Overview of Conditional Reasoning
propositional calculus
propositions
antecedent
consequent
Four Kinds of Conditional Reasoning Tasks (Table 12.1 and Demonstration 12.1)
- Affirming the antecedent means that you say the “if…” part of the sentence is true. This kind of reasoning leads to a valid, or correct, conclusion.
- The fallacy (or error) of affirming the consequent means that you say the “then…” part of the sentence is true. This kind of reasoning leads to an invalid conclusion.
- The fallacy of denying the antecedent means that you say the “if…” part of the sentence is false. Denying the antecedent also leads to an invalid conclusion.
- Denying the consequent means that you say the “then…” part of the sentence is false. This kind of reasoning leads to a correct conclusion.
Affirming the consequent causes the largest number of errors.
heuristic—a general strategy the usually works well; but ‘‘it’s a good bet’’ is not the same as ‘‘always,’’ especially in deductive reasoning
combining Type 1 and Type 2 processing
Difficulties with Linguistically Negative Information
- People take longer to evaluate problems that contain linguistically negative information.
- People are more likely to make errors on these problems.
- causesworking memory strain, especially when denying the antecedent or denying the consequent
- leads to frequent errors when translating the statement into more accessible, linguistically positive forms
Difficulties with Abstract Reasoning Problems
- People are more accurate when they solve reasoning problems that use concrete examples rather than abstract, theoretical examples.
- diagrams helpful
- Everyday knowledge may override the principles of logic.
The Belief-Bias Effect
- role of backgroundknowledge (top-down)
- belief-bias effect—when people make judgments based on prior beliefs and general knowledge, rather than on the rules of logic
- People tend to make errors when the logic of a reasoning problem conflicts with their background knowledge.
- individual differences; intelligence
- need flexible thinking to overcome the belief-bias effect
The Confirmation Bias
Are human beings rational?
The Standard Wason Selection Task
Demonstration 12.2: The Confirmation Bias—Wason's Selection Task
confirmation bias
- People tend to try to confirm or support a hypothesis rather than try to disprove it.
- In other words, people are eager to affirm the antecedent, but reluctant to deny theconsequent by searching for counterexamples.
Concrete Versions of the Wason Selection Task
replace numbers and letters with concrete situations from everyday life
People perform much better when the task is concrete, familiar, and realistic.
Griggs and Cox (1982)—drinking age example
Performance improved when task implies a social contract.
The Confirmation Bias (continued)
Applications in Medicine
People seek confirming evidence when self-diagnosing disorders (e.g., insomnia).
Both medical students and psychiatrists tend to select information consistent with their original diagnosis rather than investigate information that might be consistent with another diagnosis.
Further Perspectives
Examining our own behavior
International conflict situations
Decision Making
no established rules
no "correct" decision
interdisciplinary field
research examines concrete, realistic scenarios, rather than abstract situations
heuristics
Kahneman and Tversky
- proposed that a small number of heuristics guide human decision making
- The same strategies that normally guide us toward the correct decision may sometimes lead us astray.
The Representativeness Heuristic
coincidences
randomness
representative
representativeness heuristic
- People judge that a sample is likely if it is similar to the population from which the sample was selected.
- People believe that random-looking outcomes are more likely than orderly outcomes.
- This heuristic is so persuasive that people often ignore important statistical information that theyshould consider.
The Representativeness Heuristic (continued)
Sample Size and Representativeness
hospital babies example
A large sample is statistically more likely than a small sample to reflect the true proportions in a population.
small-sample fallacy—assume a small sample will be representative of the population from which it was selected
stereotypes
Base Rate and Representativeness
Demonstration 12.3: Base Rates and Representativeness—Tom W
base rate—how often an item occurs in the population
base-rate fallacy—emphasize representativeness and underemphasize important information about base rates
Kahneman and Tversky (1973)
- People rely on representativeness when asked to judge category membership.
- even when provided with base-rate information, people ignore it
- stereotypes
Research provides support for the dual-process approach (Type 1 and Type 2 processing).
role of training
everyday examples
The Conjunction Fallacy and Representativeness
Demonstration 12.4: Tversky and Kahneman
- "Linda is a bank teller and a feminist."
- students with different levels of statistical sophistication
- rank statements in terms of probability
conjunction rule—The probability of the conjunction of two events cannot be larger than the probability of either of its constituent events.
conjunction fallacy—when people judge the probability of the conjunction of two events to be greater than the probability of a constituent event
People tend to judge using representativeness instead of statistical probability.
Students with high SAT scores are actually more likely than other students to demonstrate the conjunction fallacy.
The Representativeness Heuristic (continued)
Summary of Representativeness Heuristic
1.We use the representativeness heuristic when we make decisions based on whether a sample looks similar in important characteristics to the population from which it is selected.
2.The representativeness heuristic is so appealing that we tend to ignore other important characteristics that we should consider, such as sample size and base rate.
3.We also fail to realize that the probability of two events occurring together (for example, bank teller and feminist) needs to be smaller than the probability of just one of those events (for example, bank teller).
The Availability Heuristic
availability heuristic—estimate frequency or probability in terms of how easy it is to think of relevant examples
only accurate when availability is correlated with true, objective frequency
can be distorted by recency and familiarity
Comparison of Representativeness and Availability Heuristics
1.If the problem is based on a judgment about similarity, you are dealing with the representativeness heuristic.
2.If the problem requires you to remember examples, you are dealing with the availability heuristic.
Recency and Availability
- Memory is better for more recent items.
- Recent items are more available.
- People judge recent items to be more likely than they really are.
MacLeod and Campbell (1992)
When people were encouraged to recall pleasant events from their past, they later judge pleasant events to be more likely in their future.
When people were encouraged to recall unpleasant events, they later judged unpleasant events to be more likely.
implications for psychotherapy
Familiarity and Availability
Brown and colleagues
population estimates for various countries
points of view shown by the media
People need to use critical thinking and shift to Type 2 processing.
The Availability Heuristic (continued)
The Recognition Heuristic
When comparing the relative frequency of two categories, if people recognize one category and not the other, they conclude that the recognized category has the higher frequency.
This strategy generally leads to an accurate decision.
Illusory Correlation and Availability
illusory correlation—People believe that two variables are statistically related, even though there is no real evidence for this relationship.
stereotypes
social cognition approach—Stereotypes can be traced to normal cognitive processes.
Chapman and Chapman (1969)
sexual orientation and inkblot responses
looking at all four cells in the matrix of possibilities (e.g., Table 12.2)
We need to specifically try to disconfirm our stereotypes.
Summary of Availability Heuristic
1.We use the availability heuristic when we estimate frequency or probability in terms of how easily we can think of examples of something. This heuristic is generally accurate in our daily lives, and people can estimate relative frequency with impressive accuracy.
2.However, availability may be contaminated by two factors that are not related to objective frequency: recency and familiarity. Therefore, when you make frequency judgments, ask yourself whether you are giving a special advantage to items that occurred more recently or that are somehow more familiar.
3.In contrast, the recognition heuristic is usually helpful when we judge relative frequency, for example, in guessing which of two cities has the larger population.
4.The availability heuristic can also create illusory correlations, when two variables appear to be correlated, although there is no statistical relationship.
The Anchoring and Adjustment Heuristic
Demonstration 12.5: The Anchoring and Adjustment Heuristic
When making an estimate, people begin with a first approximation (anchor) and then make adjustments to that number on the basis of additional information.
People rely too heavily on the anchor, and their adjustments are too small; over-influence of current hypotheses or beliefs, top-down processing
Research on the Anchoring and Adjustment Heuristic
Demonstration 12.5: Multiplication
If the first number was large, the estimates were higher than if the first number was small.
single-digit numbers anchored the estimates far too low
operates even when anchor is obviously arbitrary or impossibly extreme
operates for both novices and experts
anchor may restrict the search for relevant information in memory
applications in everyday life: courtroom sentences
Estimating Confidence Intervals
confidence interval—range within which we expect a number to fall a certain percentage of the time
Demonstration 12.6: Estimating Confidence Intervals
Studies find that, in general:
estimated confidence intervals tend to be too narrow
anchor may be erroneous and adjustments too small
people don't really understand confidence intervals
Summary of Anchoring and Adjustment
1.When we use the anchoring and adjustment heuristic, we begin by guessing a first approximation or anchor. Then we make adjustments to that anchor.
2.This heuristic is generally useful, but we typically fail to make large enough adjustments.
3.The anchoring and adjustment heuristic also explains our errors when we estimate confidence intervals; we usually supply ranges that are too narrow,given our uncertainty about the anchor.
The Framing Effect
framing effect—the outcome of a decision can be influenced by:
1)the background context of the choice
2)the way in which a question is worded
Background Information and the Framing Effect
Kahneman and Tversky (1984)—lost ticket/lost $20 study (Demonstration 12.7)
The Wording of a Question and the Framing Effect
People are distracted by surface structure of the questions.
The exact wording of a question can have a major effect on the answers.
Tversky and Kahneman (1981)—lives saved/lives lost study (Demonstration 12.8)
"lives saved" question led to more "risk averse" choices
"lives lost" question led to more "risk taking" choices
prospect theory
1.When dealing with possible gains (for example, lives saved), people tend to avoid risks.
2.When dealing with possible losses (for example, lives lost), people tend to seek risks.
The framing effect is found across many different situations.
In Depth: Overconfidence About Decisions
overconfidence—confidence judgments are higher than they should be, based on actual performance
illusory correlation
anchoring and adjustment
General Studies on Overconfidence
occurs in a variety of situations
own decisions vs. statistically observable measurements
variety of personal skills
individual differences
cross-cultural differences
In Depth: Overconfidence About Decisions (continued)
Overconfidence in Political Decision Making
sexual scandals
international conflict
failure to think systematically about the risks involved
Each side tends to overestimate its own chances of success.
Politicians are often overconfident that their data are accurate.
crystal-ball technique—imagine a completely accurate crystal ball indicates that your hypothesis is incorrect
Overconfidence About Completing Projects on Time
planning fallacy
underestimate the amount of time (or money) required to complete a project
estimate the task will be relatively easy to complete
Suggested Strategies
1.Divide your project into several parts, and estimate how long each part will take. This process will provide a more realistic estimate of the time you will need to complete the project.
2.Envision each step in the process of completing your project, such as gathering the materials, organizing the project’s basic structure, and so forth. Each day, rehearse these components.
3.Try thinking about some person other than yourself, and visualize how long this person took to complete the project; be sure to visualize the potential obstacles in your imagery.
Possible Explanations
optimistic scenario
failure to consider potential problems
memory for similar tasks
over-estimate future free time
In Depth: Overconfidence About Decisions (continued)
Reasons for Overconfidence
- People are often unaware that their knowledge is based on very tenuous and uncertain assumptions and on information from unreliable or inappropriate sources.
- Examples that confirm our hypotheses are readily available, whereas we resist searching for counterexamples.
- People have difficulty recalling the other possible hypotheses, and decision making depends on memory. If you cannot recall the competing hypotheses, you will be overly confident about the hypothesis you have endorsed.
- Even if people manage to recall the other possible hypotheses, they do not treat them seriously.
5.Researchers do not educate the public about the overconfidence problem. As a result, we typically do not pause—on the brinkof making a decision—and ask ourselves, ‘‘Am I relying only on Type 1thinking? I need to switch over to Type 2 thinking!’’
my-side bias—overconfidence that one's own view is correct in a confrontational situation; often results in conflict; cannot even consider the possibility that their opponent's position may be at least partially correct
The Hindsight Bias
hindsight—judgments about events that already happened in the past
hindsight bias—judging an event as inevitable, after the event has already happened; overconfidence that we could have predicted the outcome in advance
Research About the Hindsight Bias
Carli (1999)—judgments about people; Barbara/Jack study
happy vs. tragic ending
Both groups are confident that they could have predicted the ending.
Memory errors are consistent with the outcome.
"blame the victim"
medical diagnosis, political events, business decisions
The Hindsight Bias (continued)
Explanations for the Hindsight Bias
anchoring and adjustment
misremembering past events
Current Status of Heuristics and Decision Making
Kahneman's heuristic approach may be too pessimistic.
Harris and colleagues—People make fairly realistic judgments about future events.
Girgerenzer and colleagues
People are not perfectly rational decision makers, however people can do relatively well when they are given a fair chance.
ecological rationality—People create a wide variety of heuristics to help them make useful, adaptive decisions in the real world.
default heuristic—If there is a default option, then people will choose it.
People bring world knowledge into the research laboratory.
Both Kahneman's and Gigerenzer's approaches suggest that decision-making heuristics generally serve us well in the real world.
We can become more effective decision makers by realizing the limitations of these important strategies.
Individual Differences: Decision-Making Style and Psychological Well-Being
Maximizers—tend to examine as many options as possible (maximizing decision-making style); may lead to "choice overload"
Satisficers—tend to settle for something that is satisfactory (satisficing decision-making style)
Schwartz and coauthors (2002)—Demonstration 12.9
maximizer/satisficer scale and several other measures
students, healthcare professionals, people waiting in a train station
Maximizers tended to experience more regret following a choice than satisficers.
Maximizers tended to experience more depressive symptoms than satisficers.
More choices don't necessarily make a person happier.
Hypothetical Decision Making: How Should Wealth Be Distributed?
Norton and Ariely (2011)—How should wealth be distributed?
Demonstration 12.10
Estimates of actual and ideal distributions of wealth
Comparison of estimates with reality
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